Recovery Routing Based on Q-Learning for Satellite Network Faults

Joint Authors

Liu, Zhihui
Dong, Tao
Yin, Jie
Gu, Rentao
Qin, Jiawen

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-09-04

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Philosophy

Abstract EN

With the fierce research on the space and terrestrial network, the satellite network as the main component has received increasing attention.

Due to its special operating environment, there are temporary link failures caused by interference and permanent port failures caused by equipment problems.

In this paper, we propose a new satellite network routing technology for fault recovery based on fault detection.

Based on Bayesian decision, this technology judges the probability of each fault by a priori probability of the two faults to achieve the purpose of effectively distinguishing between two types of faults and locate faulty links and node ports.

Then, corresponding to the previous two stages of the fault detection, different stages and different methods are updated for different types of fault.

We also combine satellite network data from satellite simulation software to validate our study.

The results show that the recovery strategy has good performance, and the effective resource utilization rate is improved significantly.

American Psychological Association (APA)

Gu, Rentao& Qin, Jiawen& Dong, Tao& Yin, Jie& Liu, Zhihui. 2020. Recovery Routing Based on Q-Learning for Satellite Network Faults. Complexity،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1144735

Modern Language Association (MLA)

Gu, Rentao…[et al.]. Recovery Routing Based on Q-Learning for Satellite Network Faults. Complexity No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1144735

American Medical Association (AMA)

Gu, Rentao& Qin, Jiawen& Dong, Tao& Yin, Jie& Liu, Zhihui. Recovery Routing Based on Q-Learning for Satellite Network Faults. Complexity. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1144735

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1144735